PROJECT D: Statistical Issues in the Design and Analysis of Studies of Genetic Variants, HT and Cancer. Case-control studies are becoming increasingly complicated as exposures and host factors are being concurrently evaluated for their relationship to risk. An extraordinary amount of effort is now focused on describing variation in the human ge.nome which may be relevant to the risk of common diseases. This includes the establishment of extensive SNP databases and (very recently) an ambitious project designed to understand the patterns of linkage disequilibrium of SNPs through the development of a haplotype map of the human genome (the HapMap). The primary emphasis in this Project is the further development of statistical methods related to the use of case-control studies of unrelated subjects to assess the role that candidate genes may be playing in the risk of cancer generally and in the individual variability of response to hormone exposures specifically. All of the other planned projects in this application will be evaluating the role that candidate genes play in hormonally related cancer; in many respects the projects of this P01 are proto-typical of the "next generation" of association studies that are envisioned to be resulting shortly from the HapMap. The issues that we consider in this portion of the project are anticipated to be applicable to the full range of such studies. The second aim of this project is focused upon development and elaboration of statistical methods for dealing with the effects of exposure measurement error upon risk estimation, particularly in nested case-control studies. Our attention will be on the needs of the other planned projects and we plan initially to perform a careful analysis of the effects of measurement error in mammographic density upon the problems raised in Project D. We will continue to develop our interests in measurement error correction for epidemiological studies more broadly as well.